In the field of digital image processing, an original image, such as a photographic negative, is sampled periodically to produce a digital representation of the original image. The digital image is processed by applying image processing functions to improve such image qualities as sharpness and tone scale. The processed digital image is then displayed on output media such as a CRT or photographic film or paper.
FIG. 2 is a schematic diagram of representative image reproduction apparatus employing digital image processing. Such apparatus includes an input device 10 for sampling the original image and an analog-to-digital converter 12 for producing the digital representation of the original image. Commonly employed input devices include drum and flat bed scanners, linear and area solid state image sensing arrays, and CRT and laser flying spot scanners.
The digital image is stored in a mass memory 14, such as a solid state frame buffer, magnetic tape or disc storage device. A digital computer 16 applies the various image processing functions to the digital image to produce the processed digital image.
The digital computer 16 may comprise, for example, a main frame general purpose digital computer, or for higher speed operation, a digital computer specially configured for high speed digital processing of images.
The processed digital image is converted to sampled analog form by a digital-to-analog converter 18 and is displayed on an output device 20 such as a drum or flat bed graphic arts scanner, or a CRT or laser flying spot scanner. The elements of the image reproduction apparatus communicate via a data and control bus 22. As noted above, one of the processing functions performed by the digital computer is to adjust the tone scale and contrast of the processed image. There is a continuing effort in the field of digital image processing to automatically determine the optimum tone reproduction function and overall contrast adjustment employed by the digital computer.
The basic method of tone reproduction in digital image processing is shown graphically in FIG. 3. As shown in the upper left quadrant of the graph in FIG. 3, each input signal level (measured by the input device 10 in FIG. 1) is translated to an input tone value by an input calibration function, represented by the curve labeled 24. Each input tone value is converted to an output tone value by the tone reproduction function shown as the curve labeled 26 in the upper right quadrant of the graph. Finally, each output tone value is converted to an output device level by an output device calibration function shown by the curve labeled 28 in the lower right quadrant of the graph.
The input and output calibration functions are determined by the physical characteristics of the input and output devices and the input and output media. The optimum tone reproduction function, on the other hand, depends upon the tonal characteristics of the original image, and preferably is custom tailored for each image that is reproduced.
In the past, empirical rules for generating the tone reproduction function were derived by making a large number of reproductions using a variety of tone reproduction functions, and having a panel of observers pick the most pleasing reproduction. The selection was then correlated with the tone reproduction functions used to generate the images. Data for generating the tone reproduction function was obtained by measuring the tones in a gray scale that was recorded along with the original scene.
To automate the process of generating a tone reproduction function, it was desirable to eliminate the recorded gray scale in the original image and to seek the data needed to generate the tone reproduction function in the statistical properties of the tonal content of the original image itself.
This effort led some investigators to hypothesize that the highly modulated (busy) parts of a high quality image follow a normal (Gaussian) frequency distribution with respect to tone values. See for example U.S.S.R. Invention's Certificate No. 297976 (1971) entitled "Process for the Evaluation of the Image Quality" by Ovchinnikov et al. Ovchinnikov and his coworkers went on to demonstrate that the appearance of digitally processed photographic images could be improved by using a tone reproduction function that is generated by normalizing the distribution of a statistical sample of tone values (a lightness scale was employed) taken from parts of the image where the first derivative of lightness with respect to distance in the image was greater than some predetermined minimum threshold. See the article entitled "A New Approach to Programming in Photomechanical Reproduction" by Yu. Ovchinnikov et al. The 12th IARIGAI Conference Proc., Versailles, France, Ed. W. Banks IPC Science and Technology Press, Guildford, England 1974, pp. 160-163.
Briefly, the method of Ovchinnikov et al. involves scanning the original image and randomly sampling the tone values (lightness) occuring in parts of the image where the first derivative of lightness is above some predetermined minimum threshold value. These sampled tone values are compiled in a histogram, illustrated by the curve labeled 30 in the lower right quadrant of FIG. 4. A normal distribution is shown as the curve labeled 32 in the upper left quadrant of FIG. 4. The method for generating the tone reproduction function involves constructing a function that transforms the sampled tone distribution into the normal distribution. The optimum tone reproduction function for the whole image is then taken as that function. This tone reproduction function is shown as the curve labeled 34 in the upper right hand quadrant of FIG. 4. In this prior art method, the tone reproduction function relates each lightness value in the input to an output lightness value.
After the tone reproduction function is generated, it is applied to each tone value of the digital image to produce the processed digital image. The article by Ovchinnikov et al. does not discuss the particular lightness scale that was employed to express tone values in the tone reproduction function, nor does it disclose a method for determining the overall contrast of the processed image. The contrast of the processed image is determined by appropriately scaling the processed tone values. If an appropriate scaling is chosen that produces pleasing result for an average image, then the processed image of a scene that was illuminated by very flat lighting (skylight for example) will appear contrasty. On the other hand, processed images of scenes with an exceptionally long tone scales will appear too flat. If the contrast of the processed image must be adjusted by an operator making subjective judgements about the original images, this prevents the use of the digital processing method in fully automated photographic printing apparatus. This represents a shortcoming of the method.
It is therefore an object of the present invention to provide a method of automatically adjusting the overall contrast in a digital image processing method of the type employing a tone reproduction function generated by normalizing a sample of tone values from the informational portion of the image.